Manager - Software Engineering

Actively participate in:

System design and architecture decisions

API design and microservices standards

Code reviews for critical components

Guide teams on:

Java + Spring Boot microservices architecture

Event-driven systems (Kafka or equivalent)

Scalable frontend design using React + TypeScript

Ensure systems meet expectations for:

Scalability

Performance

Security (especially PHI/PII handling)

Reliability

This is NOT a “review PPT and attend meetings” role. If you can’t deep-dive into code/design when needed, you will struggle.

Drive adoption of AI tools (Copilot, Windsurf) across engineering teams to:

Improve engineering velocity

Reduce boilerplate work

Accelerate testing and documentation

Establish guardrails for AI usage:

No blind copy-paste from AI-generated code

Mandatory validation for correctness, security, and performance

Encourage AI-assisted testing and debugging

Ensure teams build:

Well-structured APIs and systems that are AI-consumable

Observable systems (logs, metrics, traces) that enable intelligent diagnostics

Hire strong engineers in a highly competitive India market

Build a high-performance culture (not just high headcount)

Mentor engineers across levels:

Technical growth (design, coding, debugging)

Career progression

Ownership mindset

Handle:

Performance management

Low performance correction

Offshore/onshore collaboration

Own end-to-end delivery across:

Backend services

APIs

UI integrations

Data flows

Enforce:

CI/CD discipline

Testing rigor (unit + integration)

Release quality standards

Partner with:

Product Managers

QA teams

DevOps / Platform teams

10–15 years of software engineering experience

Strong hands-on experience with:

Java + Spring Boot (microservices, REST APIs)

React.js + TypeScript

Experience with:

Distributed systems / microservices architecture

SQL databases (Oracle/Postgres)

Event-driven systems (Kafka or similar)

Strong debugging and production issue handling skills

3–5 years of engineering management experience

Proven track record of:

Hiring strong engineers

Managing and mentoring teams

Delivering complex projects

Candidates must demonstrate :

Practical use of AI coding assistants in development workflow

Ability to review, validate , and production-harden AI-generated code

Enforce engineering discipline in an AI-assisted environment

If someone treats AI as autocomplete and not as a productivity and innovation multiplier with accountability — they won’t fit.

Team consistently delivers high-quality, production-ready features

Strong engineering culture with low defect leakage and high ownership

Engineers effectively use AI to move faster without lowering standards

Systems built are:

Scalable

Observable

Reusable

Build real-world healthcare systems impacting patient outcomes

Work on modern architecture + AI-driven engineering workflows

Opportunity to shape engineering culture and standards at scale

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